The Essential Mathematics for Computer Science specialisation provides the fundamental toolkit needed to excel in computing, data science, and software engineering. Across five courses, you will progress from core mathematical foundations to advanced topics that underpin modern computer science. You’ll begin with sets, number systems, functions, and relations, move into advanced mathematical methods such as algebra, vectors, combinatorics, and probability, then explore geometry, trigonometry, and calculus for modelling motion and change. The pathway continues with logic and reasoning, where you’ll master propositional and predicate logic, Boolean algebra, and proof strategies, before concluding with algorithms and complexity, analysing efficiency, recursion, and computational limits.
By completing this specialisation, you will gain industry-relevant skills in discrete mathematics, logic, algebra, calculus, probability, and algorithmic reasoning. These competencies prepare you to design efficient algorithms, analyse complexity, reason formally, and apply mathematical methods to real computing challenges. Whether your goal is to pursue further study in computer science, strengthen your programming and problem-solving skills, or advance in fields such as data science, artificial intelligence, or systems design, this specialisation ensures you have the rigorous mathematical foundation that employers and universities expect.
Applied Learning Project
Throughout this specialisation, you will complete hands-on projects that allow you to apply mathematical reasoning directly to computing challenges. You’ll design and manipulate sets to model data, convert and analyse number systems in binary and hexadecimal, and build functions and relations to describe structured problems. Later projects involve applying algebra, probability, and combinatorics to analyse scenarios, using trigonometry and calculus to model motion and optimisation, and employing logic, Boolean algebra, and proof strategies to verify correctness. In the capstone projects, you will analyse algorithms, test efficiency, and reason about complexity, mirroring the way computer scientists approach real-world problems. By engaging with these authentic tasks, you will not only practise theoretical concepts but also demonstrate the ability to solve computational problems with clarity, precision, and industry-relevant methods.
